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Comment by RuiWang0811 | Hacker News Reader

this seems to be a common misconception, our envs use market data, but the goal is not (only) trading. Market data just happens to be a good source of hard data science tasks.

Re trading: I’d argue there is no such thing as solving investment nor is there “the one profitable strategy”. Every decision from personal risk appetite to trading horizon changes what is the optimal strategy for you and there are multiple strategies that make money.

Also note that even the most profitable alphas are no crystal balls. Someone else mentioned 5% correlation to future return - depending on horizon and data such level of correlation can make 9 figure PnL and is by no means easy to achieve

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What's the margins that makes this worth chasing then? That's the part I maybe don't quite understand, why would you pour a lot of money and resources into something that is stochastic at best?

Quant trading is an extremely high margin business itself. Quant shops are printing billions and have on average much higher profits per employee than tech companies. So it is definitely a business worth doing.

On the other hand, you could also view quant research as some very hard research problems, so training LLMs on these problems could also enhance their general research capabilities.

Right, that's quant trading, that's not this business. Enhancing their research seems like they are your customer and you would be eating from their margin.

How would you sell to them, you would deliver what? Faster time to decision? Wouldn't quants be your competition, given their work is building tools like this one?

No we sell our own research to AI labs as RL envs. Realistic RL envs grows in demand as labs seek better data train better models.

It’s a complimentary business. Simply put: we sell envs to labs, labs make better models, firms buy these models to make more profit. Everybody wins.

Yeah a competitor for us would be fellow quants doing the same thing. But even then every quant firm trades differently (and good ones all make money) so envs can still be sufficiently different.

So what's an example today of "envs" like yours that these firms buy and how you differ from them? Why you?

there are loads of env businesses for coding tasks, enterprise tasks, computer use etc etc. we offer different envs from a niche industry, which just so happens to be a very hard data science task & where the data doesn't saturate. In order to build these you'd need niche expert knowledge.

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